Back in 2011, IBM pitted its Artificial Intelligence (A.I.) technology, Watson, against reigning Jeopardy champions Ken Jennings and Brad Rutter. To come out ahead of its human competitors, Watson’s win required 20 dedicated researchers, devoting 3 years of their lives, and the equivalent of 200 million pages of information.
A.I. is only as good as the raw material feeding it — that raw material being data. While we’ve come a long way since Watson’s victory, organizations still face some pretty steep challenges to A.I. implementation. Turning data into actionable insights that can drive intelligent decision-making means organizations have to consolidate their information and more importantly, provide context to their data.
Quite simply, data and knowledge are not the same thing.
In order for A.I. to extract meaning, predict outcomes, and prescribe action, companies need to transform their raw operational data into learnable knowledge.
It’s about putting ALL their information to work. But organizations have proven less than adept at corralling their disparate information. Box, Amazon and Microsoft are delivering A.I. solutions but first need users to push content into their specific repositories. We've seen how well that goes. ECMs still only manage a tiny sliver of enterprise information with the vast majority of it — upwards to 90% — scattered across disconnected business systems and content repositories. Companies still struggle with how to transfer data from operational systems, distributed repositories, and users’ desktops to analytical systems.
We help put the Big back into Big Data. Sure, we can consolidate your documents to a single repository — we're technologically agnostic so it doesn't matter if you're using one or all of OneDrive, Box or AWS. Keep information wherever it makes the most sense, we work to identify what’s there because having content isn’t enough. You need context. Data labeling, improved metadata and complex analysis provide you with the building blocks needed to power predictive and prescriptive tools. Find your documents where they are and identify what they are with zero user disruption.
In order for A.I. to live up to the current hype we can’t just rely on a handful of data scientists to feed information into a single closed system. We've seen where that path leads. Everyone needs to be contributing across the organization, regardless of where the information is created, stored or archived. Once that happens the potential impact to business value fuelled by A.I. will be completely disruptive.